Statistical method of solar components

How to predict solar power generation?

Traditional prediction methods, such as statistical regression models, time-series analysis, and physical modeling, have been used to forecast solar power generation based on factors like solar irradiance, temperature, and humidity .

How accurate is solar yield forecasting?

Traditional methods of solar yield prediction, including statistical approaches and simple regression models, often fail to capture the complex, nonlinear relationships between these variables, leading to suboptimal accuracy in forecasting .

Does principal component analysis reduce dimensionality in solar radiation prediction models?

Accurate solar radiation prediction is essential for optimizing renewable energy systems and supporting grid stability. This study investigates the use of principal component analysis (PCA) for dimensionality reduction in solar radiation prediction models, followed by an evaluation of the models’ performance across varying feature sets.

Can modelled data be used to inform opinion on solar projects?

There is a distinct lack of infrastructure re-sources in the country to collect long-term measured data, hence it is necessary to use modelled data to inform opinion on solar projects (Pegels, 2010; Msimanga and Sebitosi, 2014).